Course Descriptions (Undergrad)

STA 010—Statistical Thinking (4)

Lecture—3 hour(s); Discussion/Laboratory—1 hour(s). Prerequisite(s): Two years of high school algebra. Statistics and probability in daily life. Examines principles of collecting, presenting and interpreting data in order to critically assess results reported in the media; emphasis is on understanding polls, unemployment rates, health studies; understanding probability, risk and odds. GE credit: QL, SE. Effective: 2000 Spring Quarter.

STA 012—Introduction to Discrete Probability (4)

Lecture—3 hour(s); Laboratory—1 hour(s). Prerequisite(s): Two years of high school algebra. Random experiments; countable sample spaces; elementary probability axioms; counting formulas; conditional probability; independence; Bayes theorem; expectation; gambling problems; binomial, hypergeometric, Poisson, geometric, negative binomial and multinomial models; limiting distributions; Markov chains. Applications in the social, biological, and engineering sciences. GE credit: QL, SE. Effective: 1999 Fall Quarter.

STA 013—Elementary Statistics (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): Two years of high school algebra or Mathematics D. Descriptive statistics; basic probability concepts; binomial, normal, Student's t, and chi-square distributions. Hypothesis testing and confidence intervals for one and two means and proportions. Regression. Not open for credit for students who have completed STA 013V, or higher. GE credit: QL, SE. Effective: 2016 Fall Quarter.

STA 013Y—Elementary Statistics (4)

Lecture—1.5 hour(s); Web Virtual Lecture—5 hour(s). Prerequisite(s): Two years of high school algebra or Mathematics D. Descriptive statistics; basic probability concepts; binomial, normal, Student's t, and chi-square distributions. Hypothesis testing and confidence intervals for one and two means and proportions. Regression. Not open for credit for students who have completed STA 013, or higher. GE credit: QL, SE. Effective: 2016 Fall Quarter.

STA 032—Gateway to Statistical Data Science (4)

Lecture—3 hour(s); Laboratory—1 hour(s). Prerequisite(s): MAT 016B or MAT 021B or MAT 017B. Probability concepts; programming in R; exploratory data analysis; sampling distribution; estimation and inference; linear regression; simulations; resampling methods. Alternative to Statistics 13 for students with a background in calculus and programming. Only two units of credit allowed to students who have taken STA 013; not open for credit to students who have taken STA 100. GE credit: QL, SE. Effective: 2018 Winter Quarter.

STA 090X—Seminar (1-2)

Seminar—1-2 hour(s). Prerequisite(s): Consent of Instructor. High school algebra. Examination of a special topic in a small group setting. Effective: 1997 Winter Quarter.

STA 098—Directed Group Study (1-5)

Variable. Prerequisite(s): Consent of Instructor. (P/NP grading only.) Effective: 1997 Winter Quarter.

STA 099—Special Study for Undergraduates (1-5)

Variable. Prerequisite(s): Consent of Instructor. (P/NP grading only.) Effective: 2000 Spring Quarter.

STA 100—Applied Statistics for Biological Sciences (4)

Lecture—3 hour(s); Laboratory—1 hour(s). Prerequisite(s): MAT 016B or MAT 017B or MAT 021B. Descriptive statistics, probability, sampling distributions, estimation, hypothesis testing, contingency tables, ANOVA, regression; implementation of statistical methods using computer package. Only two units credit allowed to students who have taken STA 013, STA 032 or 103; not open for credit to students who have taken STA 102. GE credit: QL, SE. Effective: 2017 Spring Quarter.

STA 101—Advanced Applied Statistics for the Biological Sciences (4)

Lecture—3 hour(s); Laboratory—1 hour(s). Prerequisite(s): STA 100. Basic experimental designs, two-factor ANOVA without interactions, repeated measures ANOVA, ANCOVA, random effects vs. fixed effects, multiple regression, basic model building, resampling methods, multiple comparisons, multivariate methods, generalized linear models, Monte Carlo simulations. GE credit: QL, SE. Effective: 2014 Fall Quarter.

STA 103—Applied Statistics for Business and Economics (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): (STA 013 or STA 013Y or STA 032 or STA 100); (MAT 016B or MAT 017B or MAT 021B). Descriptive statistics; probability; random variables; expectation; binomial, normal, Poisson, other univariate distributions; joint distributions; sampling distributions, central limit theorem; properties of estimators; linear combinations of random variables; testing and estimation; Minitab computing package. Two units credit to students who have completed STA 100. GE credit: QL, SE. Effective: 2018 Winter Quarter.

STA 104—Applied Statistical Methods: Nonparametric Statistics (4)

Lecture—3 hour(s); Laboratory—1 hour(s). Prerequisite(s): STA 013 or STA 013Y or STA 032 or STA 100. Sign and Wilcoxon tests, Walsh averages. Two-sample procedures. Inferences concerning scale. Kruskal-Wallis test. Measures of association. Chi square and Kolmogorov-Smirnov tests. GE credit: QL, SE. Effective: 2018 Winter Quarter.

STA 106—Applied Statistical Methods: Analysis of Variance (4)

Lecture—3 hour(s); Discussion/Laboratory—1 hour(s). Prerequisite(s): STA 013 or STA 013Y or STA 032 or STA 100. Basics of experimental design. One-way and two-way fixed effects analysis of variance models. Randomized complete and incomplete block design. Multiple comparisons procedures. One-way random effects model. GE credit: SE. Effective: 2018 Winter Quarter.

STA 108—Applied Statistical Methods: Regression Analysis (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): STA 013 or STA 013Y or STA 032 or STA 100. Simple linear regression, variable selection techniques, stepwise regression, analysis of covariance, influence measures, computing packages. GE credit: QL, SE, SL. Effective: 2018 Winter Quarter.

STA 130A—Mathematical Statistics: Brief Course (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): MAT 016C or MAT 017C or MAT 021C. Basic probability, densities and distributions, mean, variance, covariance, Chebyshev's inequality, some special distributions, sampling distributions, central limit theorem and law of large numbers, point estimation, some methods of estimation, interval estimation, confidence intervals for certain quantities, computing sample sizes. Only 2 units of credit allowed to students who have taken STA 131A. GE credit: QL, SE.Effective: 2018 Winter Quarter.

STA 130B—Mathematical Statistics: Brief Course (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): STA 130A or STA 131A or MAT 135A. Transformed random variables, large sample properties of estimates. Basic ideas of hypotheses testing, likelihood ratio tests, goodness-of- fit tests. General linear model, least squares estimates, Gauss-Markov theorem. Analysis of variance, F-test. Regression and correlation, multiple regression. Selected topics. GE credit: QL, SE. Effective: 2016 Fall Quarter.

STA 131A—Introduction to Probability Theory (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): MAT 021B; MAT 021C; MAT 022A or MAT 067. Fundamental concepts of probability theory, discrete and continuous random variables, standard distributions, moments and moment-generating functions, laws of large numbers and the central limit theorem. Not open for credit to students who have completed MAT 135A. GE credit: QL, SE. Effective: 2018 Winter Quarter.

STA 131B—Introduction to Mathematical Statistics (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): STA 131A or MAT 135A; or Consent of Instructor. Sampling, methods of estimation, bias-variance decomposition, sampling distributions, Fisher information, confidence intervals, and some elements of hypothesis testing. GE credit: SE. Effective: 2017 Winter Quarter.

STA 131C—Introduction to Mathematical Statistics (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): STA 131B; or Consent of Instructor. Testing theory, tools and applications from probability theory, Linear model theory, ANOVA, goodness-of-fit. GE credit: SE. Effective: 2016 Fall Quarter.

STA 135—Multivariate Data Analysis (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): (STA 130B or STA 131B); (MAT 022A or MAT 067). Multivariate normal distribution; Mahalanobis distance; sampling distributions of the mean vector and covariance matrix; Hotellings T2; simultaneous inference; one-way MANOVA; discriminant analysis; principal components; canonical correlation; factor analysis. Intensive use of computer analyses and real data sets. GE credit: QL, SE. Effective: 2016 Fall Quarter.

STA 137—Applied Time Series Analysis (4)

Lecture—3 hour(s); Laboratory—1 hour(s). Prerequisite(s): STA 108. Time series relationships; univariate time series models: trend, seasonality, correlated errors; regression with correlated errors; autoregressive models; autoregressive moving average models; spectral analysis: cyclical behavior and periodicity, measures of periodicity, periodogram; linear filtering; prediction of time series; transfer function models. GE credit: QL, SE. Effective: 2016 Fall Quarter.

STA 138—Analysis of Categorical Data (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): (STA 130B or STA 131B) or (STA 106, STA 108). Varieties of categorical data, cross-classifications, contingency tables, tests for independence. Multidimensional tables and log-linear models, maximum likelihood estimation; tests of goodness-of-fit. Logit models, linear logistic models. Analysis of incomplete tables. Packaged computer programs, analysis of real data. GE credit: QL, SE. Effective: 1997 Winter Quarter.

STA 141A—Fundamentals of Statistical Data Science (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): (STA 108 or STA 106); (STA 032 or STA 100 or STA 013 or STA 013Y). Introduction to computing for data analysis and visualization, and simulation, using a high-level language (e.g., R). Computational reasoning, computationally intensive statistical methods, reading tabular and non-standard data. Not open for credit to students who have taken STA 141 or STA 242. Effective: 2018 Spring Quarter.

STA 141B—Data & Web Technologies for Data Analysis (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): STA 141A. Pass One and Pass Two restricted to Statistics majors and graduate students in Statistics and Biostatistics. Open to all students during Open Registration. Essentials of using relational databases and SQL. Processing data in blocks. Scraping Web pages and using Web services/APIs. Basics of text mining. Interactive data visualization with Web technologies. Computational data workflow and best practices. Statistical methods. Effective: 2019 Winter Quarter.

STA 141C—Big Data & High Performance Statistical Computing (4)

Lecture—3 hour(s); Discussion—1 hour(s). Prerequisite(s): STA 141B or (STA 141A, ECS 010). Pass One and Pass Two restricted to Statistics majors and graduate students in Statistics and Biostatistics; open to all students during Open registration. High-performance computing in high-level data analysis languages; different computational approaches and paradigms for efficient analysis of big data; interfaces to compiled languages; R and Python programming languages; high-level parallel computing; MapReduce; parallel algorithms and reasoning. Effective: 2019 Winter Quarter.

STA 144—Sampling Theory of Surveys (4)

Lecture—3 hour(s); Discussion/Laboratory—1 hour(s). Prerequisite(s): (STA 130B or STA 131B) or (STA 106, STA 108). Simple random, stratified random, cluster, and systematic sampling plans; mean, proportion, total, ratio, and regression estimators for these plans; sample survey design, absolute and relative error, sample size selection, strata construction; sampling and nonsampling sources of error. GE credit: QL, SE. Effective: 2016 Fall Quarter.

STA 145—Bayesian Statistical Inference (4)

Lecture—3 hour(s); Laboratory—1 hour(s). Prerequisite(s): STA 130B or STA 131B. Subjective probability, Bayes Theorem, conjugate priors, non-informative priors, estimation, testing, prediction, empirical Bayes methods, properties of Bayesian procedures, comparisons with classical procedures, approximation techniques, Gibbs sampling, hierarchical Bayesian analysis, applications, computer implemented data analysis. GE credit: QL, SE. Effective: 2016 Fall Quarter.

STA 160—Practice in Statistical Data Science (4)

Lecture—3 hour(s); Discussion/Laboratory—1 hour(s). Prerequisite(s): STA 106; STA 108; (STA 130B or STA 131B); (STA 141 or STA 141A). Principles and practice of interdisciplinary, collaborative data analysis; complete case study review and team data analysis project. Effective: 2016 Spring Quarter.

STA 190X—Seminar (1-2)

Seminar—1-2 hour(s). Prerequisite(s): STA 013 or STA 013Y or STA 032 or STA 100 or STA 103. In-depth examination of a special topic in a small group setting. Effective: 2018 Spring Quarter.

STA 192—Internship in Statistics (1-12)

Internship—3-36 hour(s); Term Paper. Prerequisite(s): Consent of Instructor. Upper division standing. Work experience in statistics. (P/NP grading only.) Effective: 1997 Winter Quarter.

STA 194HA—Special Studies for Honors Students (4)

Independent Study—12 hour(s). Prerequisite(s): Senior qualifying for honors. Directed reading, research and writing, culminating in the completion of a senior honors thesis or project under direction of a faculty advisor. GE credit: SE. Effective: 1997 Winter Quarter.

STA 194HB—Special Studies for Honors Students (4)

Independent Study—12 hour(s). Prerequisite(s): Senior qualifying for honors. Directed reading, research and writing, culminating in the completion of a senior honors thesis or project under direction of a faculty advisor. GE credit: SE. Effective: 1997 Winter Quarter.

STA 198—Directed Group Study (1-5)

Variable. Prerequisite(s): Consent of Instructor. (P/NP grading only.) Effective: 1997 Winter Quarter.

STA 199—Special Study for Advanced Undergraduates (1-5)

Variable. Prerequisite(s): Consent of Instructor. (P/NP grading only.) Effective: 1997 Winter Quarter.